Machines that learn from experience.
IncySpeak is a semantic-memory runtime for machines. An IncySpeak machine takes in experience, grounds it into entities and predicates, stores it as episodic memory, accumulates evidence over time, and forms semantic beliefs that it can predict from, revise, and explain.
The learning pipeline
| 1. experience | Raw input observed from configured sources. |
| 2. language / event perception | Text and events are parsed into structured signals. |
| 3. entity / predicate grounding | Signals are grounded to subjects, predicates, and objects. |
| 4. episodic memory | Grounded observations are stored with time and provenance. |
| 5. evidence accumulation | Repeated support and counter-evidence are weighed. |
| 6. semantic beliefs | Stable statements emerge with a confidence and stage. |
| 7. prediction / revision / provenance | Beliefs drive predictions and can be revised and explained. |
What this site is
This repository is only the cloud side of IncySpeak:
- the public IncySpeak website;
- the authenticated web control plane; and
- the cloud coordination / API layer for remote IncySpeak machines.
The semantic engine itself is not part of this site. It runs separately on ARM64 machines, which keep ownership of their local episodic and semantic memory. See how it works and the developer notes.